This m-function returns the beta-geometric probability density function with parameters A and B at the values in X. Note: The density function is zero unless A and B are integers.The Beta-geometric distribution is used to model the number of failures that will occur in a binomial proccess before...
Platforms: Matlab

This m-file returns the beta-binomial probability density function with parameters N, A and B at the values in X. Note: The density function is zero unless N, A and B are integers.The Beta-binomial distribution is used to model the number of successes in n binomial trials when the probability of...
Platforms: Matlab

This m-function returns the negative hypergeometric probability density function with parameters M, N and A at the values in X. Note: The density function is zero unless M, N and A are integers.If a lot consists of M acceptable items and N defective ones. Suppose that items are drawn at random...
Platforms: Matlab

RanLip uses acceptance/rejection approach to generate random vectors, which is based on approximation of the probability density function from above with a "hat" function. It is assumed that the distribution hasLipschitz-continuous density, which is either given analytically or has a black box....
Platforms: Matlab

PDFPLOT displays a histogram of the empirical probability density function (PDF) for the data in the input array X using nbins number of bins.If input X is a matrix, then pdfplot(X) parses it to the vector and displays PDF of all values.For complex input X, pdfplot(X) displays PDF of...
Platforms: Matlab

This m-file returns the multinomial probability density function value with parameters N and P at the values in X. Note that the density function is zero unless X is an integer.Let {X1, X2, . . . , Xk}, k > 1, be a set of random variables, each of which can take the values 0, 1, . . . , n....
Platforms: Matlab

This m-file returns the multivariate hypergeometric probability density function at M with integer parameters in N. Note: The density function is zero unless the elements in M are integers.If there are m_i elements of class i in a population and you take n elements at random without replacement,...
Platforms: Matlab

The Metropolis-Hastings Sampler is the most common Markov-Chain-Monte-Carlo (MCMC) algorithm used to sample from arbitrary probability density functions (PDF). Suppose you want to simulate samples from a random variable which can be described by an arbitrary PDF, i.e., any function which...
Platforms: Windows, Mac, *nix, Python, BSD Solaris

This code implements and plots the exact numerical solution of the Ornstein-Uhlenbeck process and its time integral. The numerical method here used was published by D.T. Gillespie in 1996 in the journal Physical Review E.The probability density function and its plot for the Ornstein-Uhlenbeck...
Platforms: Matlab

Functions for Rice/Rician PDF: summary statistics (mean and variance), generating random samples, and simple moment-matching to fit the distribution to data.Similar to e.g. normpdf, normstat, normrnd and normfit from the MATLAB statistics toolbox, but for the Rice distribution, which is useful in...
Platforms: Matlab

The files in this folder contains small routines for MATLAB to compute and plot triangular probability denstity function. There are following 4 files:tglpdf : Compute and plot triangular probability density function for given value of X (X can be scalar or matrix)tglcdf : Compute and plot...
Platforms: Matlab

The QM Probability program displays the time evolution of the position-space wave function and the associated probability density. The default wave function is the n = 5 state in a ramped infinite square well. Additional states and other potential energy functions can be specified using the...
Platforms: Mac

This function implements bivariant Gaussian kernel density estimation. It can be used to estimate bivariant probability density function (pdf), cumulative distribution function (cdf) and inversed cdf (icdf) from a set of random data. The code is programmed in a way to be suitable for beginners to...
Platforms: Matlab